Design Patterns in software development and MQL5 (Part 4): Behavioral Patterns 2
In this article, we will complete our series about the Design Patterns topic, we mentioned that there are three types of design patterns creational, structural, and behavioral. We will complete the remaining patterns of the behavioral type which can help set the method of interaction between objects in a way that makes our code clean.
How to create a custom indicator (Heiken Ashi) using MQL5
In this article, we will learn how to create a custom indicator using MQL5 based on our preferences, to be used in MetaTrader 5 to help us read charts or to be used in automated Expert Advisors.
Trade Events in MetaTrader 5
A monitoring of the current state of a trade account implies controlling open positions and orders. Before a trade signal becomes a deal, it should be sent from the client terminal as a request to the trade server, where it will be placed in the order queue awaiting to be processed. Accepting of a request by the trade server, deleting it as it expires or conducting a deal on its basis - all those actions are followed by trade events; and the trade server informs the terminal about them.
Timeseries in DoEasy library (part 35): Bar object and symbol timeseries list
This article starts a new series about the creation of the DoEasy library for easy and fast program development. In the current article, we will implement the library functionality for accessing and working with symbol timeseries data. We are going to create the Bar object storing the main and extended timeseries bar data, and place bar objects to the timeseries list for convenient search and sorting of the objects.
Simulink: a Guide for the Developers of Expert Advisors
I am not a professional programmer. And thus, the principle of "going from the simple to the complex" is of primary importance to me when I am working on trading system development. What exactly is simple for me? First of all, it is the visualization of the process of creating the system, and the logic of its work. Also, it is a minimum of handwritten code. In this article, I will attempt to create and test the trading system, based on a Matlab package, and then write an Expert Advisor for MetaTrader 5. The historical data from MetaTrader 5 will be used for the testing process.
The Inverse Fair Value Gap Trading Strategy
An inverse fair value gap(IFVG) occurs when price returns to a previously identified fair value gap and, instead of showing the expected supportive or resistive reaction, fails to respect it. This failure can signal a potential shift in market direction and offer a contrarian trading edge. In this article, I'm going to introduce my self-developed approach to quantifying and utilizing inverse fair value gap as a strategy for MetaTrader 5 expert advisors.
Another MQL5 OOP Class
This article shows you how to build an Object-Oriented Expert Advisor from scratch, from conceiving a theoretical trading idea to programming a MQL5 EA that makes that idea real in the empirical world. Learning by doing is IMHO a solid approach to succeed, so I am showing a practical example in order for you to see how you can order your ideas to finally code your Forex robots. My goal is also to invite you to adhere the OO principles.
Analyzing charts using DeMark Sequential and Murray-Gann levels
Thomas DeMark Sequential is good at showing balance changes in the price movement. This is especially evident if we combine its signals with a level indicator, for example, Murray levels. The article is intended mostly for beginners and those who still cannot find their "Grail". I will also display some features of building levels that I have not seen on other forums. So, the article will probably be useful for advanced traders as well... Suggestions and reasonable criticism are welcome...
Using MetaTrader 5 as a Signal Provider for MetaTrader 4
Analyse and examples of techniques how trading analysis can be performed on MetaTrader 5 platform, but executed by MetaTrader 4. Article will show you how to create simple signal provider in your MetaTrader 5, and connect to it with multiple clients, even running MetaTrader 4. Also you will find out how you can follow participants of Automated Trading Championship in your real MetaTrader 4 account.
Applying OLAP in trading (part 3): Analyzing quotes for the development of trading strategies
In this article we will continue dealing with the OLAP technology applied to trading. We will expand the functionality presented in the first two articles. This time we will consider the operational analysis of quotes. We will put forward and test the hypotheses on trading strategies based on aggregated historical data. The article presents Expert Advisors for studying bar patterns and adaptive trading.
Creating an EA that works automatically (Part 02): Getting started with the code
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we discussed the first steps that anyone needs to understand before proceeding to creating an Expert Advisor that trades automatically. We considered the concepts and the structure.
Data Science and Machine Learning — Neural Network (Part 01): Feed Forward Neural Network demystified
Many people love them but a few understand the whole operations behind Neural Networks. In this article I will try to explain everything that goes behind closed doors of a feed-forward multi-layer perception in plain English.
Automating Trading Strategies in MQL5 (Part 5): Developing the Adaptive Crossover RSI Trading Suite Strategy
In this article, we develop the Adaptive Crossover RSI Trading Suite System, which uses 14- and 50-period moving average crossovers for signals, confirmed by a 14-period RSI filter. The system includes a trading day filter, signal arrows with annotations, and a real-time dashboard for monitoring. This approach ensures precision and adaptability in automated trading.
Automating Trading Strategies in MQL5 (Part 44): Change of Character (CHoCH) Detection with Swing High/Low Breaks
In this article, we develop a Change of Character (CHoCH) detection system in MQL5 that identifies swing highs and lows over a user-defined bar length, labels them as HH/LH for highs or LL/HL for lows to determine trend direction, and triggers trades on breaks of these swing points, indicating a potential reversal, and trades the breaks when the structure changes.
Universal Expert Advisor: Trading in a Group and Managing a Portfolio of Strategies (Part 4)
In the last part of the series of articles about the CStrategy trading engine, we will consider simultaneous operation of multiple trading algorithms, will learn to load strategies from XML files, and will present a simple panel for selecting Expert Advisors from a single executable module, and managing their trading modes.
CatBoost machine learning algorithm from Yandex with no Python or R knowledge required
The article provides the code and the description of the main stages of the machine learning process using a specific example. To obtain the model, you do not need Python or R knowledge. Furthermore, basic MQL5 knowledge is enough — this is exactly my level. Therefore, I hope that the article will serve as a good tutorial for a broad audience, assisting those interested in evaluating machine learning capabilities and in implementing them in their programs.
Neural networks made easy (Part 11): A take on GPT
Perhaps one of the most advanced models among currently existing language neural networks is GPT-3, the maximal variant of which contains 175 billion parameters. Of course, we are not going to create such a monster on our home PCs. However, we can view which architectural solutions can be used in our work and how we can benefit from them.
The Last Crusade
Take a look at your trading terminal. What means of price presentation can you see? Bars, candlesticks, lines. We are chasing time and prices whereas we only profit from prices. Shall we only give attention to prices when analyzing the market? This article proposes an algorithm and a script for point and figure charting ("naughts and crosses") Consideration is given to various price patterns whose practical use is outlined in recommendations provided.
Testing patterns that arise when trading currency pair baskets. Part I
We begin testing the patterns and trying the methods described in the articles about trading currency pair baskets. Let's see how oversold/overbought level breakthrough patterns are applied in practice.
How to build and optimize a cycle-based trading system (Detrended Price Oscillator - DPO)
This article explains how to design and optimise a trading system using the Detrended Price Oscillator (DPO) in MQL5. It outlines the indicator's core logic, demonstrating how it identifies short-term cycles by filtering out long-term trends. Through a series of step-by-step examples and simple strategies, readers will learn how to code it, define entry and exit signals, and conduct backtesting. Finally, the article presents practical optimization methods to enhance performance and adapt the system to changing market conditions.
Automating Trading Strategies in MQL5 (Part 43): Adaptive Linear Regression Channel Strategy
In this article, we implement an adaptive Linear Regression Channel system in MQL5 that automatically calculates the regression line and standard deviation channel over a user-defined period, only activates when the slope exceeds a minimum threshold to confirm a clear trend, and dynamically recreates or extends the channel when the price breaks out by a configurable percentage of channel width.
Using the TesterWithdrawal() Function for Modeling the Withdrawals of Profit
This article describes the usage of the TesterWithDrawal() function for estimating risks in trade systems which imply the withdrawing of a certain part of assets during their operation. In addition, it describes the effect of this function on the algorithm of calculation of the drawdown of equity in the strategy tester. This function is useful when optimizing parameter of your Expert Advisors.
Learn how to design a trading system by Awesome Oscillator
In this new article in our series, we will learn about a new technical tool that may be useful in our trading. It is the Awesome Oscillator (AO) indicator. We will learn how to design a trading system by this indicator.
Automating Trading Strategies in MQL5 (Part 37): Regular RSI Divergence Convergence with Visual Indicators
In this article, we build an MQL5 EA that detects regular RSI divergences using swing points with strength, bar limits, and tolerance checks. It executes trades on bullish or bearish signals with fixed lots, SL/TP in pips, and optional trailing stops. Visuals include colored lines on charts and labeled swings for better strategy insights.
Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design
There are minor things to cover on the feed-forward neural network before we are through, the design being one of them. Let's see how we can build and design a flexible neural network to our inputs, the number of hidden layers, and the nodes for each of the network.
Engineering Trading Discipline into Code (Part 1): Creating Structural Discipline in Live Trading with MQL5
Discipline becomes reliable when it is produced by system design, not willpower. Using MQL5, the article implements real-time constraints—trade-frequency caps and daily equity-based stops—that monitor behavior and trigger actions on breach. Readers gain a practical template for governance layers that stabilize execution under market pressure.
Developing Zone Recovery Martingale strategy in MQL5
The article discusses, in a detailed perspective, the steps that need to be implemented towards the creation of an expert advisor based on the Zone Recovery trading algorithm. This helps aotomate the system saving time for algotraders.
Neural Networks in Trading: A Multi-Agent Self-Adaptive Model (MASA)
I invite you to get acquainted with the Multi-Agent Self-Adaptive (MASA) framework, which combines reinforcement learning and adaptive strategies, providing a harmonious balance between profitability and risk management in turbulent market conditions.
Developing a cross-platform grider EA (part III): Correction-based grid with martingale
In this article, we will make an attempt to develop the best possible grid-based EA. As usual, this will be a cross-platform EA capable of working both with MetaTrader 4 and MetaTrader 5. The first EA was good enough, except that it could not make a profit over a long period of time. The second EA could work at intervals of more than several years. Unfortunately, it was unable to yield more than 50% of profit per year with a maximum drawdown of less than 50%.
Neural networks made easy (Part 12): Dropout
As the next step in studying neural networks, I suggest considering the methods of increasing convergence during neural network training. There are several such methods. In this article we will consider one of them entitled Dropout.
Library for easy and quick development of MetaTrader programs (part XVI): Symbol collection events
In this article, we will create a new base class of all library objects adding the event functionality to all its descendants and develop the class for tracking symbol collection events based on the new base class. We will also change account and account event classes for developing the new base object functionality.
Universal Regression Model for Market Price Prediction
The market price is formed out of a stable balance between demand and supply which, in turn, depend on a variety of economic, political and psychological factors. Differences in nature as well as causes of influence of these factors make it difficult to directly consider all the components. This article sets forth an attempt to predict the market price on the basis of an elaborated regression model.
Automating Trading Strategies in MQL5 (Part 25): Trendline Trader with Least Squares Fit and Dynamic Signal Generation
In this article, we develop a trendline trader program that uses least squares fit to detect support and resistance trendlines, generating dynamic buy and sell signals based on price touches and open positions based on generated signals.
Gradient Boosting (CatBoost) in the development of trading systems. A naive approach
Training the CatBoost classifier in Python and exporting the model to mql5, as well as parsing the model parameters and a custom strategy tester. The Python language and the MetaTrader 5 library are used for preparing the data and for training the model.
Automating Trading Strategies in MQL5 (Part 8): Building an Expert Advisor with Butterfly Harmonic Patterns
In this article, we build an MQL5 Expert Advisor to detect Butterfly harmonic patterns. We identify pivot points and validate Fibonacci levels to confirm the pattern. We then visualize the pattern on the chart and automatically execute trades when confirmed.
Statistical Carry Trade Strategy
An algorithm of statistical protection of open positive swap positions from unwanted price movements. This article features a variant of the carry trade protection strategy that allows to compensate for potential risk of the price movement in the direction opposite to that of the open position.
Developing a trading Expert Advisor from scratch (Part 7): Adding Volume at Price (I)
This is one of the most powerful indicators currently existing. Anyone who trades trying to have a certain degree of confidence must have this indicator on their chart. Most often the indicator is used by those who prefer “tape reading” while trading. Also, this indicator can be utilized by those who use only Price Action while trading.
Visualizing trading strategy optimization in MetaTrader 5
The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.
Library for easy and quick development of MetaTrader programs (part XII): Account object class and collection of account objects
In the previous article, we defined position closure events for MQL4 in the library and got rid of the unused order properties. Here we will consider the creation of the Account object, develop the collection of account objects and prepare the functionality for tracking account events.
Price Action Analysis Toolkit Development (Part 44): Building a VWMA Crossover Signal EA in MQL5
This article introduces a VWMA crossover signal tool for MetaTrader 5, designed to help traders identify potential bullish and bearish reversals by combining price action with trading volume. The EA generates clear buy and sell signals directly on the chart, features an informative panel, and allows for full user customization, making it a practical addition to your trading strategy.